In modem manufacturing processes, it is generally desirable to provide as much control and automation as possible. In order to improve the processes as much as possible, and to provide as great a control as possible, large amounts of information are collected and analyzed that allow for refinement of the process and improve quality control.
For example, during a semiconductor manufacturing process, a large number of sensors can be used to monitor the processes and provide sensoric data to a processor. The data is processed and analyzed and adjustments are made to the processes as necessary based upon that analysis. The processor's analysis produces results that indicate values corresponding to a particular wafer that is either currently being processed or has been processed. The values are compared to known process parameters used in creating a “golden wafer”, i.e., a desirable wafer. Statistical analysis yields the conformity of the examined process to the process that created the “golden wafer”. If some parameter of the process is out of range, such that the process is not being properly performed, the values produced by the processor's statistical analysis will indicate this condition. At that point, an operator can modify the process for that particular wafer or in future wafer processing.
A problem with this approach is the need for a human operator to interpret the numerical value results and take appropriate action based upon the numbers provided by this statistical analysis of the processor. This is difficult to achieve in real time during the processing of the wafer, and also does not provide an intuitive feel to the operator as to when the process is not being performed properly.
There is a need for a system having a graphical user interface that provides a user with an intuitive feel for whether a process is being performed within acceptable limits.